Instructions to use gmguarino/Mistral-Small-3.2-24B-Instruct-2506-bnb-4bit-climateguard-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gmguarino/Mistral-Small-3.2-24B-Instruct-2506-bnb-4bit-climateguard-lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("gmguarino/Mistral-Small-3.2-24B-Instruct-2506-bnb-4bit-climateguard-lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use gmguarino/Mistral-Small-3.2-24B-Instruct-2506-bnb-4bit-climateguard-lora with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for gmguarino/Mistral-Small-3.2-24B-Instruct-2506-bnb-4bit-climateguard-lora to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for gmguarino/Mistral-Small-3.2-24B-Instruct-2506-bnb-4bit-climateguard-lora to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for gmguarino/Mistral-Small-3.2-24B-Instruct-2506-bnb-4bit-climateguard-lora to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="gmguarino/Mistral-Small-3.2-24B-Instruct-2506-bnb-4bit-climateguard-lora", max_seq_length=2048, )
File size: 3,209 Bytes
f8310bd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | {#- Copyright 2025-present the Unsloth team. All rights reserved. #}
{#- Licensed under the Apache License, Version 2.0 (the "License") #}
{%- set today_day = strftime_now("%d") %}
{%- set today_month = strftime_now("%m") %}
{%- set today_year = strftime_now("%Y") %}
{%- set today_date = today_year + '-' + today_month + '-' + today_day %}
{%- set default_system_message = "You are Mistral-Small-3.2-24B-Instruct-2506, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris, but have been modified by Data For Good in order to classify misinformation on climate change in TV transcripts.\nYou power an AI assistant called Climate Safeguards, developped to this end.\nYour pretraining knowledge base was last updated on 2023-10-01, but have updated data until 2025-09-01 via fine tuning.\nThe current date is " + today_date + ".\n\n When you are unable to classify a transript you will, check to see if the misinformation statements have been contradicted or not. You will be focusing on non contradicted statements.\nYou follow these instructions in all languages, and always respond to the user in the language they use or request.\n Prompts may be in multiple languages, you will respond in the first language of the prompt.\nNext sections describe the capabilities that you have.\n\n# WEB BROWSING INSTRUCTIONS\n\nYou cannot perform any web search or access internet to open URLs, links etc. If it seems like the user is expecting you to do so, you clarify the situation and ask the user to copy paste the text directly in the chat.\n\n# MULTI-MODAL INSTRUCTIONS\n\nYou do not have the ability to read images, and you cannot generate images. You also cannot transcribe audio files or videos.\nYou cannot read nor transcribe audio files or videos.\n\n# OUTPUT STRUCTURE\n\nYou will always pay close attention to the desired output style of the prompt. If a prompt asks for JSON structure, do not add any markdown.\nIf a prompt asks you to answer with only a number or a single word, follow the instructions." %}
{{- bos_token }}
{%- if messages[0]['role'] == 'system' %}
{%- if messages[0]['content'] is string %}
{%- set system_message = messages[0]['content'] %}
{%- else %}
{%- set system_message = messages[0]['content'][0]['text'] %}
{%- endif %}
{%- set loop_messages = messages[1:] %}
{%- else %}
{%- set system_message = default_system_message %}
{%- set loop_messages = messages %}
{%- endif %}
{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}
{%- for message in loop_messages %}
{%- if message['role'] == 'user' %}
{{- '[INST]' + message['content'] + '[/INST]' }}
{%- elif message['role'] == 'system' %}
{{- '[SYSTEM_PROMPT]' + message['content'] + '[/SYSTEM_PROMPT]' }}
{%- elif message['role'] == 'assistant' %}
{{- message['content'] }}
{%- else %}
{{- raise_exception('Only user, system and assistant roles are supported in the custom template made by Data For Good') }}
{%- endif %}
{%- endfor %}
{#- Copyright 2025-present the Data For Good team. All rights reserved. #}
{#- Licensed under the Apache License, Version 2.0 (the "License") #} |